Posts

hugging face o colab

Image
High-level overview of how to run LLM models Prerequisite: Transformers NLP Python  Huggingface Suppose you have a problem statement related to text generation to proceed with it we want to search for a text generation model that would suffice our needs. Step 1: Search for open-source LLM models on platforms like:  HuggingFace Step 2: Select for your specific task model you want to fetch Step 3: Select any model for testing Step 4: Suppose we chose phi-2 model by microsoft Step 5: There is a sample code provided for the usage of the model copy in colab and use it Notebook link
Post a Comment
Read more

Gen ai Evloution

Image
Generative AI services excel in generating diverse content types beyond text, including images, music, and code. On the other hand, LLMs are tailored for text-based tasks such as natural language understanding, text generation, language translation, and textual analysis. Open-source LLMs and Private LLMs
Post a Comment
Read more

flask basics

  What is Flask? Flask is a micro web framework written in Python. It’s called a "micro" framework because it provides the essential tools to build web applications without imposing any dependencies or project layout. This makes Flask lightweight and flexible, allowing developers to add extensions as needed. Key Features of Flask: Lightweight and modular. Built-in development server and debugger. RESTful request dispatching. Jinja2 templating. Support for secure cookies. Setting Up Flask Before we dive into the code, let's set up Flask. Here’s how you can install Flask: Install Python: Make sure Python is installed on your system. You can download it from python.org . Install Flask: Open your terminal or command prompt and run: pip install Flask Create a Project Directory: Create a directory for your project and navigate into it:  cd my_flask_app Create a Virtual Environment:  python -m venv venv              venv\Scripts\a...
Post a Comment
Read more

Exploring LLMs and APIs: The Journey to Choosing Gemini API for GiftGuru

 Exploring LLMs and APIs: The Journey to Choosing Gemini API for GiftGuru In the realm of artificial intelligence, choosing the right tools and technologies can significantly impact the success of a project. As I embarked on the journey to develop GiftGuru, a platform for personalized gift recommendations, I explored various Large Language Models (LLMs) and APIs to find the perfect fit. 1. Exploring Different LLMs Gemma Overview: Gemma is known for its robust language understanding capabilities. Pros: It excels in text comprehension and contextual understanding. Cons: However, it lacked the generative capabilities needed for creating unique and diverse gift suggestions. Ollama Overview: Ollama focuses on conversational AI and dialogue generation. Pros: It was impressive in generating interactive responses. Cons: Its performance in generating product-specific recommendations was less consistent. Phi3 Overview: Phi3 is designed for complex language tasks. Pros: It handled int...
Post a Comment
Read more

overview of gen ai

Image
 Overview of GEN AI Artificial Intelligence (AI) has become an integral part of our daily lives, from smart assistants like Siri and Alexa to personalized recommendations on Netflix and Amazon. One fascinating branch of AI is Generative AI, which has the remarkable ability to create content—be it text, images, music, or even entire virtual environments. What is Generative AI? Generative AI refers to a type of artificial intelligence that can generate new content. Unlike traditional AI models that simply classify data or make predictions, Generative AI models can create novel outputs based on the data they’ve been trained on. This can include writing a poem, composing a piece of music, creating a digital painting, or even generating human-like conversations. How Does Generative AI Work? At its core, Generative AI works by learning patterns from vast amounts of data and then using that knowledge to generate new content. Here’s a simplified breakdown of the process: Data Collection: ...
Post a Comment
Read more

Pricing

Image
 Pricing Gemini api Cloud platforms
Post a Comment
Read more

modeldeploy

Image
 Model deployment of LLAMA2 7b Model deployment steps: Understand the Model: Before deploying an LLM, it’s important to understand its capabilities, limitations, and the specific use case it will serve. Choose the Right Platform: Decide whether you want to deploy the model locally or on a cloud platform. Each has its own advantages and disadvantages. Prepare the Model: This could involve fine-tuning the model on your specific task or data1. Set Up the Infrastructure: This involves setting up the servers or cloud resources where the model will run. You’ll need to consider the computational resources required by the model. Deploy the Model: Use a model serving tool or platform to deploy the model. This could be a cloud service or an open-source tool. Ensure Security and Privacy: Implement measures to ensure the security of the model and the privacy of the data it handles. Monitor the Model: Once the model is deployed, monitor its performance and usage to ensure it’s working as expect...
Post a Comment
Read more